Big Data
Related Technologies, Challenges and Future Prospects
Del i serien SpringerBriefs in Computer Science
718 kr
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Beskrivning
Produktinformation
- Utgivningsdatum:2014-05-15
- Mått:155 x 235 x 6 mm
- Vikt:178 g
- Format:Häftad
- Språk:Engelska
- Serie:SpringerBriefs in Computer Science
- Antal sidor:89
- Upplaga:2014
- Förlag:Springer International Publishing AG
- ISBN:9783319062440
Utforska kategorier
Recensioner i media
"The book not only provides readers with a fundamental understanding of big data, but also points to many future research topics and directions. ... it covers comprehensive aspects of big data and provides abundant references. I believe that it will be a valuable resource for researchers working with big data, especially those working in computer science, computer engineering, or related fields." (I-Lun Tseng, Computing Reviews, June, 2015) "This book provides a big picture in this broad research area, covering all the phases of its value chains. ... The book presents an overview on different phrases of big data value chain. ... I would like to recommend this book to researchers and industrial practitioners who work with big data, and it is also useful for researchers in relevant areas such as parallel computing, NoSQL Database, machine learning and data analytics." (Gang Li, Information Technology and Tourism, Vol. 15, 2015) "The authors' knowledge of information and communications technology (ICT) and teaching experience allow them to give a very good comprehensive overview of big data and related themes, providing a thorough and timely exploration of this broad new field. ... Each chapter starts with an abstract, and then the themes are demonstrated from many perspectives in the following sections. ... I recommend this introductory book ... for those who want to understand problems and solutions regarding big data." (K. Balogh, Computing Reviews, November, 2014)
Innehållsförteckning
- Introduction.- Related Technologies.- Big Data Generation and Acquisition.- Big Data Storage.- Big Data Analysis.- Big Data Applications.- Open Issues and Outlook.
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